Why SaaS businesses need a reboot in the age of Agentic AI
The Software as a Service (SaaS) model has defined enterprise software for decades, bringing speed, flexibility, and scalability to every business function imaginable. With the rise of Agentic AI, SaaS is heading into a new era – one that will require a reboot of business models, writes Puneet Vyas, Director at TH Global Capital.
SaaS is a cloud-based delivery model where software applications are hosted by a provider and accessed over the internet, usually via a subscription. It eliminates the need for users to install, maintain, or update software locally, providing on-demand access from any compatible device.
Agentic AI – autonomous AI systems capable of acting, learning, and orchestrating complex workflows – is poised to transform SaaS, leading to an ecosystem marked by overlap and reinvention.
The 2024 SaaS Benchmarks Report shows that 56% of SaaS vendors have launched or tested embedded AI features; 41% are monetizing them – up 9% from 2023.
The results of this transition are telling. Dashboards are giving way to conversational UI, consumers and employees are being supported by zero-friction agent workflows, and we are seeing the rise of outcome-based automation.
The transformation of SaaS models
But as generative and agentic workflows proliferate, SaaS companies must innovate to remain central in the stack – or risk being bypassed by more flexible, customizable agent-led architectures.
Complete displacement is unlikely – but significant disruption is inevitable in some domains:
Outcome-first workflows
In some functions (customer support, sales automation, workflow orchestration), agentic AI already eclipses static SaaS. Businesses may rationalise back-end systems into unified repositories, and AI agents will directly access and act on this data—sometimes removing the need for distinct SaaS applications
Custom generative SaaS
Low-code/no-code platforms let teams build AI-driven tools that mimic SaaS at lower cost, tailored to each workflow
Regulatory, complexity, and value moat
Where compliance, reliability, or deep integrations are paramount, SaaS incumbents with rich data, strong ecosystems, and customer trust maintain a durable edge.
What should SaaS companies do?
Adapt, don’t retreat. Thriving in the agentic AI era means SaaS companies should embed Agentic AI as a core capability, re-architect for higher autonomy, and prioritise transparency and trust. They should also experiment with new business models and invest in hybrid governance strategies.
For investors, the transformation that Agentic AI will unleash means that they should more closely evaluate whether a SaaS company owns defensible data, offers compelling agentic workflows, and has the ability to adapt – these are core signals of resilience and growth.
Conclusion
The age of Agentic SaaS is here and it is here to stay. SaaS is not dying – it’s being rebooted. Expect continued coexistence, with agentic AI enhancing, extending, and sometimes replacing classic SaaS workflows. Winners will be those who adapt quickly, blend autonomy with trust, and reimagine software less as a static service – and more as a proactive, collaborative teammate.
